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| Section | Weight | Objectives |
|---|---|---|
| Data Quality Concepts and Principles | 15% | - Definition and importance of data quality - Data quality dimensions - Data quality in DMBOK framework |
| Data Quality Assessment and Profiling | 25% | - Defining quality rules and metrics - Data profiling techniques - Assessment methods and tools |
| Data Quality Strategy and Governance | 20% | - Roles and responsibilities - Integration with data governance - Data quality strategy and policy |
| Data Quality Improvement | 20% | - Root cause analysis - Monitoring and continuous improvement - Data cleansing and standardization |
| Tools, Techniques and Implementation | 20% | - Business value and ROI - Data quality in lifecycle management - Data quality tools and technologies |
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問題 #79
A business case for adding a new master data management solution is dependent on achieving greater value from:
答案:B
問題 #80
Critical to the incremental development of the data warehouse is:
答案:A
解題說明:
A strong Release Management process is critical when a Data Warehouse evolves incrementally. DAMA- DMBOK2 states directly that Release Management supports incremental development by coordinating new capabilities, enhancements, production deployment, and recurring maintenance of deployed warehouse assets.
A Data Warehouse is rarely completed in one implementation. Business requirements evolve, additional subject areas are onboarded, models are extended, transformation rules change, new reports are introduced, and defects are corrected. Release Management provides the controlled mechanism for packaging these changes into predictable production increments.
This requires prioritization of the backlog, coordination between business and technical teams, regression testing, deployment control, documentation, reconciliation, and validation of new or changed data structures.
Without disciplined release management, incremental development can produce incompatible transformations, unstable reports, inconsistent historical treatment, and uncontrolled changes to definitions.
Data Quality should therefore form part of each release gate. New mappings and transformations should be profiled and reconciled; quality thresholds should be retested; metadata and lineage must be updated; and known exceptions should be documented.
Agile development may be used as a delivery method, but DAMA specifically identifies Release Management as the process critical to sustaining incremental warehouse evolution.
Reference Topics: DAMA-DMBOK2 Data Warehousing and Business Intelligence - Maintain Data Products; Release Management; Incremental Development; Chapter 13 - Quality Monitoring and Change Control.
問題 #81
In data security, which of the following is not one of the four A's:
答案:D
解題說明:
Agile is not one of the four A's of Data Security. DAMA security guidance groups core security processes around Access, Audit, Authentication, and Authorization. These capabilities collectively control who can interact with information resources, establish identity, determine permitted actions, and provide evidence of activity for monitoring and accountability. DAMA-aligned security references identify these four concepts directly.
Authentication confirms the identity of a user or system. Authorization determines what an authenticated identity is permitted to do. Access concerns the actual ability to obtain or interact with data and services.
Audit provides traceability by recording and reviewing relevant activities.
Agile, by contrast, is an approach to iterative delivery and project or product development. It may influence how security controls are implemented within development lifecycles, but it is not itself one of the foundational security-control categories identified in this model.
Data Security and Data Quality are separate but related disciplines. Unauthorized modifications can compromise accuracy and integrity, while weak auditability can prevent organizations from identifying how data was altered. Appropriate security controls therefore help preserve the reliability of governed information.
Metadata classification also supports these controls by identifying sensitive data and linking it to access and protection requirements.
Reference Topics: DAMA-DMBOK2 Chapter 7 - Data Security; Access; Authentication; Authorization; Audit; Data Governance; Chapter 13 - Integrity and Controlled Data Modification.
問題 #82
The Family Name of a Person is recorded in a system. The column name is Pname. Pname is an example of:
答案:E
解題說明:
Pname is Metadata because it is the name assigned to a database column and therefore describes the structure in which the actual Family Name values are stored. A value such as Smith or Patel would be data; Pname is structural information describing that data.
DAMA-DMBOK2 defines Metadata broadly as information about data and data-related processes. Technical metadata includes physical database characteristics such as table names, column names, datatypes, lengths, indexes, constraints, and related structural properties. The interpretation of Pname as metadata is also consistent with the published version of this exact certification question.
The fact that Pname may be an unclear abbreviation does not change its classification. It may represent a poor naming convention from a usability or governance perspective, but technically it remains metadata. A stronger physical name might be FamilyName, while the metadata repository could additionally map that field to the authoritative business glossary term.
This distinction matters to Data Quality because rules are frequently attached to metadata objects. For example, the Family Name attribute might have completeness, permitted-character, maximum-length, and standardization requirements.
Effective Metadata Management connects the technical column to its business meaning, system lineage, stewardship, and applicable Data Quality controls.
Reference Topics: DAMA-DMBOK2 Chapter 11 - Technical Metadata; Database Metadata; Business Glossary; Chapter 13 - Data Quality Rules and Metadata.
問題 #83
One way of defining ethics is:
答案:D
解題說明:
The correct principle is "Doing it right when no one is looking." The statement captures the essential distinction between ethical behaviour and mere compliance. Ethical conduct does not depend on observation, enforcement, or the probability of being caught; it requires responsible action because the action itself is appropriate. The answer wording is presented directly in the PDF on page 4.
DAMA-DMBOK2 treats data ethics as an essential component of professional Data Management because organizations routinely make choices about collecting, combining, analyzing, retaining, sharing, and monetizing data. A technically permissible activity may still create inappropriate effects on individuals or expose data to potential misuse.
Data ethics therefore extends beyond security and regulatory compliance. It requires consideration of the impact on people, potential for misuse, and economic value of data. Ethical handling also requires transparency concerning data provenance, intended use, quality limitations, and the consequences of decisions based on data.
Data Quality has an ethical dimension as well. Knowingly using inaccurate, incomplete, misleading, or poorly understood data in consequential decisions can harm customers and other stakeholders. Governance should therefore establish not only compliance controls but also principles for responsible use.
Reference Topics: DAMA-DMBOK2 Chapter 2 - Data Handling Ethics; Ethical Principles; Impact on People; Potential for Misuse; Chapter 13 - Reliable and Fit-for-Purpose Data.
問題 #84
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DAMA的DQ-1220的考試認證對每位IT人士來說都是非常重要的,只要得到這個認證你一定不回被職場淘汰,並且你將會被升職,加薪。有了這些現實的東西,你將得到你想要的一切,有人說,通過了DAMA的DQ-1220的考試認證就等於走向了成功,沒錯,這是真的,你有了你想要的一切就是成功的表現之一。VCESoft的 DAMA的DQ-1220的考題資料是你們成功的源泉,有了這個培訓資料,只會加快你們成功的步伐,讓你們成功的更有自信,也是保證讓你們成功的砝碼。
DQ-1220資料: https://www.vcesoft.com/DQ-1220-pdf.html